Parameter estimation in image processing and computer vision. (English) Zbl 1269.65023
Bock, Hans Georg (ed.) et al., Model based parameter estimation. Theory and applications. Based on the workshop on parameter estimation, Heidelberg, Germany, 2009. Berlin: Springer (ISBN 978-3-642-30366-1/hbk; 978-3-642-30367-8/ebook). Contributions in Mathematical and Computational Sciences 4, 311-334 (2013).
Summary: Parameter estimation plays a dominant role in a wide number of image processing and computer vision tasks. In these settings, parameterizations can be as diverse as the application areas. Examples of such parameters are the entries of filter kernels optimized for a certain criterion, image features such as the velocity field, or part descriptors or compositions thereof. Subsequently, approaches for estimating these parameters encompass a wide range of techniques, often tuned to the application, the underlying data and viable assumptions. Here, an overview of parameter estimation in image processing and computer vision is given. Due to the wide and diverse areas in which parameter estimation is applicable, this review does not claim completeness. Based on selected key topics in image processing and computer vision, we discuss parameter estimation, its relevance, and give an overview over the techniques involved.
For the entire collection see [Zbl 1261.65002].
For the entire collection see [Zbl 1261.65002].
MSC:
| 65D19 | Computational issues in computer and robotic vision |
| 65D18 | Numerical aspects of computer graphics, image analysis, and computational geometry |
| 94A08 | Image processing (compression, reconstruction, etc.) in information and communication theory |
| 62F10 | Point estimation |
| 65C60 | Computational problems in statistics (MSC2010) |
Software:
SIFTReferences:
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